numerous problems encountered in real life cannot be actually formulated as a single objective problem; hence the requirement of multi-objective optimization (moo) had arisen several years ago. due to the complexities in such type of problems powerful heuristic techniques were needed, which has been strongly satisfied by swarm intelligence (si) techniques. particle swarm optimization (pso) has ...

efficient and on-time maintenance plays a crucial role inreducing cost and increasing the market share of an industrial unit. preventivemaintenance is a broad term that encompasses a set of activitiesaimed at improving the overall reliability and availability of a systembefore machinery breakdown. the previous studies have addressed thescheduling of preventive maintenance. these studies have co...

Multi-objective optimisation problems normally have not one but a set of solutions, which are called Pareto-optimal solutions or non-dominated solutions. Once a Pareto-optimal set has been obtained, the decision-maker faces the challenge of analysing a potentially large set of solutions. Selecting one solution over others can be quite a challenging task because the Pareto set can contain an unm...

a multi-objective optimization procedure has been developed to determine some kinetic parameters of free radical polymerization of vinyl acetate based on genetic algorithm. for this purpose, mathematical modeling of free radical polymerization of vinyl acetate is carried out first and then selected kinetic parameters are optimized by minimizing objective functions defined from comparing experim...

Most engineering optimization uses multiple objective functions rather than single objective function. To realize an artificial life algorithm based multi-objective optimization, this paper proposes a Pareto artificial life algorithm that is capable of searching Pareto set for multi-objective function solutions. The Pareto set of optimum solutions is found by applying two objective functions fo...

  We suggest a method for finding the non-dominated points of the production possibility set (PPS) with variable returns to scale (VRS) technology in data envelopment analysis (DEA). We present a multiobjective linear programming (MOLP) problem whose feasible region is the same as the PPS under variable returns to scale for generating non-dominated points. We demonstrate that Pareto solutions o...

A genetic algorithm for multiobjective optimization is presented which tries to evolve an evenly distributed set of solutions belonging to the Pareto set by: (i) ranking the population according to nondomination properties; (ii) defining a filter to retain Pareto set solutions and (iii) using adequate operators: exclusion, addition and single-objective operator which improves the individuals fr...

In multidisciplinary optimization a designer solves a problem where there are different criteria usually contradicting each other. In general, the solution of such a problem is not unique. When seeking an optimal design, it is natural to exclude from the consideration any design solution which can be improved without deterioration of any discipline and violation of the constraints; in other wor...

This paper proposes a Trust-Region Based Augmented Method (TRALM) to solve a combined Environmental and Economic Power Dispatch (EEPD) problem. The EEPD problem is a multi-objective problem with competing and non-commensurable objectives. The TRALM produces a set of non-dominated Pareto optimal solutions for the problem. Fuzzy set theory is employed to extract a compromise non-dominated sol...